Update app.py

app.py

@@ -4,7 +4,7 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
 
-API_URL = "https://14d0-34-27-134-153.ngrok-free.app/query"  # Replace with your ngrok public URL
+API_URL = "https://7eba-34-127-95-74.ngrok-free.app/query"  
 
 st.set_page_config(
     page_title="SQL Agent with Streamlit", 
@@ -15,34 +15,52 @@ st.set_page_config(
 with st.sidebar:
     st.write("## About Me")
     st.write("**Mahmoud Hassanen**") 
-    st.write("**[LinkedIn Profile](https://www.linkedin.com/in/mahmoudhassanen99//)**")
-    
+    st.write("**[LinkedIn Profile](https://www.linkedin.com/in/mahmoudhassanen99/)**")
+
+# Main content
 st.title("SQL Agent with Streamlit")
 st.header("Analyze Sales Data with Natural Language Queries")
 
 # Input for the question
 question = st.text_input("Enter your question:")
 
-if st.button("Submit"):
+if st.button("Generate SQL"):
     if question:
+        # API to generate SQL
         response = requests.post(API_URL, json={"question": question})
         
         if response.status_code == 200:
             data = response.json()
-            st.write("Generated SQL Query:")
-            st.code(data["sql_query"], language="sql")
-            
-            st.write("Query Results:")
-            result_df = pd.read_json(data["result"], orient='records')
-            st.dataframe(result_df)
-            
-            # Visualize the data
-            if 'region' in result_df.columns and 'total_sales' in result_df.columns:
-                st.write("Total Sales by Region")
-                fig, ax = plt.subplots()
-                sns.barplot(x='region', y='total_sales', data=result_df, ax=ax)
-                st.pyplot(fig)
+            generated_sql = data["sql_query"]
+            st.session_state.generated_sql = generated_sql  # Store the generated SQL in session state
+            st.write("### Generated SQL Query:")
+            st.code(generated_sql, language="sql")
         else:
-            st.error(f"Error: {response.json().get('error')}")
+            st.error(f"API Error: Status Code {response.status_code}")
     else:
-        st.warning("Please enter a question.")
+        st.warning("Please enter a question.")
+
+# Allow the user to modify the SQL query
+if "generated_sql" in st.session_state:
+    modified_sql = st.text_area("Modify the SQL query (if needed):", st.session_state.generated_sql, height=200)
+    
+    if st.button("Execute Modified Query"):
+        try:
+            # Execute the modified SQL query
+            response = requests.post(API_URL, json={"sql_query": modified_sql})  # Send the modified SQL to the API
+            if response.status_code == 200:
+                data = response.json()
+                result_df = pd.read_json(data["result"], orient='records')
+                st.write("### Query Results:")
+                st.dataframe(result_df)
+                
+                # Visualize the data (if applicable)
+                if 'region' in result_df.columns and 'total_sales' in result_df.columns:
+                    st.write("### Total Sales by Region")
+                    fig, ax = plt.subplots()
+                    sns.barplot(x='region', y='total_sales', data=result_df, ax=ax)
+                    st.pyplot(fig)
+            else:
+                st.error(f"Error executing SQL: {response.json().get('error')}")
+        except Exception as e:
+            st.error(f"Error executing SQL: {e}")